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Supervised classification in remote sensing imagery is receiving increasing attention in current research. In order to improve the classification ability, a lot of spatial-features have been utilized. Unfortunately, too many features often cause classifier over-fit to a certain features' character and lead to lower classification accuracy. Feature selection algorithms have utilized to select useful...
Discretization of continuous-valued attributes is always one of the key problems in rough sets theory, a multiscale rough set model (MRSM) is developed that describes the discretization at multiple scales and analyzes the relation of classifications and certainty between scales. In view of the model's efficiency and effectiveness. an optimal scale can be acquired with self-organization, self-study...
In the scheme of Pawlak rough derivatives theory, functional features of roughly derived functions and higher order roughly derived functions are directed in rough function model. The valuing laws of first order and higher order roughly derived functions are given in form of a rough derivatives table. According to the difference principle of numerical analysis theory, the higher order rough derivative...
In this paper, the properties of the inclusion degree and similarity degree of L-fuzzy sets are presented. On the basis, the inclusion degree and similarity degree of fuzzy rough sets are defined. The generating methods of the inclusion degree and similarity degree of fuzzy rough sets are presented, through the proved properties of the inclusion degree and similarity degree. Finally, the generating...
Moxibustion is one of treatment methods which are commonly used in clinical Chinese medicine, with several thousand years of history. However, many factors affect the curative effect of moxibustion, such as the meridians and acupoints selection, the time of moxibustion, the amount of moxibustion and so on. there is a lot of uncertain information, lacking of regularity of the excavation, which has...
In an ordered decision information system, dominance-based rough set approach (DRSA) were used to compute reducts of the system which preserve the lower and upper approximations of upward union and downward union of decision classes. Recently, class-based reducts (L-reduct and U-reduct) which preserve respectively lower and upper approximates of each decision classes was proposed. In this paper, we...
The veracity of land evaluation is tightly related to the reasonable weights of land evaluation factors. A new method is proposed for determining land evaluation factors by combining the subjective and objective weights based on rough sets mining theory in this paper. Objective weight is obtained based on the rough sets theory. On the basis of the experience knowledge and practical applications, decision-makers...
The extension of classical rough set model is a very hot and interesting topic. In this paper, our aim is to present the first type of graded rough set (FGRS) based on rough membership function. The concepts of k-regions, k-rough degree, etc., are proposed firstly, and some of important properties are investigated in this rough set model. Moreover, the model has the corresponding properties with classical...
Learning from imbalanced data sets presents a new challenge to machine learning community, as traditional methods are biased to majority classes and produce poor detection rate of minority classes. This paper presents a new approach, namely fuzzy-rough k-nearest neighbor algorithm for imbalanced data sets learning to improve the classification performance of minority class. The approach defines fuzzy...
First, we classify the objects in continuous domain decision table according to fuzzy clustering; then, combining rough set theory with fuzzy set theory, an attribute reduct algorithm of decision table with continuous attributes is put forward; at last, a rule extraction algorithm is proposed and also the validity of this algorithm is accounted for through an example.
Medical data often contains a large number of irrelevant and redundant features and a relatively small number of cases, which dramatically impact quality of diseases diagnosis. Hence, in quest for higher differentiation quality, feature selection is expected to improve differentiation performance. In this paper, we describe a heuristic approach based on Rough Sets theory and information theory, for...
In Object-Oriented Data Base (OODB), attributions and methods are encapsulated together to form class and the instances of class form object. Affected by methods, the attribute values of the object are changing constantly settling in or moving out of the sets. The object sets being studied become bidirectional DS-sets. By analyzing the characteristic of class and S-rough set, the object-oriented DS-rough...
Roughness is an important uncertainty measure for a concept in an information system. By introducing a definition of α-knowledge granulation, a new uncertainty measure, called α-knowledge granulation based roughness (α-GKR), of a set is proposed in this paper. And then, MGKR, a special case of α-GKR measure, is deduced. It is generalized from the Pawlak's roughness and has two significant properties...
The paper studies the axiomatization of rough sets with a new approach, that is, the matroidal approach. First, Pawlak matroids are introduced. Properties of Pawlak matroids are studied. Then three sets of axioms of the Pawlak upper approximation operator are proposed from a matroidal point of view. Additionally, a possible generalization of Pawlak rough sets based on coverings is pointed out.
Rough sets theory can be used to research imprecise and incomplete problems in information systems. Conflict analysis and resolution play an important role in business, governmental, political and lawsuits disputes, labor-management negotiations, military operations and others. This article illustrates the proposed approach by means of a simple tutorial example of voting analysis in conflict situations...
In this paper, we introduce the concept of θs, which is the transmissing expression of a reflexive relation θ on domain X, study the topological properties of generalized rough set (X, θ) and get some interesting results. These results will be not only conducive to better understanding of some basic concepts and properties in rough set theory, but also have theory and actual significance to topology.
The purpose of this paper is to establish sample classification algorithms in consistent and inconsistent decision tables. First, according to the definition of inclusion degree and the idea of positive region in rough set, we give the definition of set value vector inclusion degree; then, according to the maximum inclusion degree principle, the sample classification algorithms are put forward with...
Attribute reduction is one of the key problems in Rough Set theory, and many algorithms have been proposed for static data. Very little work has been done in incremental attribute reduction algorithm. In this paper, an incremental attribute reduction algorithm is present. In order to reduce the computational complexity, a fast counting sort algorithm is introduced for dealing with redundant and inconsistent...
By the combination of feature and concept hierarchy model and the definition of innovation about concept, the method of structured processing and knowledge hierarchical representation for injection mould repair schemes is put forward under the condition of non-fuzzy or fuzzy data. Rule sets can be provided by knowledge induction for injection mould repairs based on basic rough set, but the rule sets...
It is very hard to acquire the information what you really want with the accumulation of large amount of data. Data mining technology has been achieved a great progress with the rapid development of computer science, artificial intelligence, and warehouse. City planning is a job with strong subjective which promotes the development of digital city planning. This makes an increasing demand of data...
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